Forestvoltaics,Floatovoltaics and Building Applied Photovoltaics(BAPV)Potential for a University Campus

The United Nations’Sustainable Development Goals(SDGs)highlight the importance of affordable and clean energy sources.Solar energy is a perfect example,being both renewable and abundant.Its popularity shows no signs of slowing down,with solar photovoltaic(PV)panels being the primary technology for converting sunlight into electricity.Advancements are continuously being made to ensure cost-effectiveness,high-performing cells,extended lifespans,and minimal maintenance requirements.This study focuses on identifying suitable locations for implementing solar PVsystems at theUniversityMalaysia PahangAl SultanAbdullah(UMPSA),Pekan campus including buildings,water bodies,and forest areas.A combined technical and economic analysis is conducted using Helioscope for simulations and the Photovoltaic Geographic Information System(PVGIS)for economic considerations.Helioscope simulation examine case studies for PV installations in forested areas,lakes,and buildings.This approach provides comprehensive estimations of solar photovoltaic potential,annual cost savings,electricity costs,and greenhouse gas emission reductions.Based on land coverage percentages,Floatovoltaics have a large solar PV capacity of 32.3 Megawatts(MW);forest-based photovoltaics(Forestvoltaics)achieve maximum yearly savings of RM 37,268,550;and Building Applied Photovoltaics(BAPV)have the lowest CO2 emissions and net carbon dioxide reduction compared to other plant sizes.It also clarifies the purpose of using both software tools to achieve a comprehensive understanding of both technical and economic aspects.

Analysis for Effects of Temperature Rise of PV Modules upon Driving Distance of Vehicle Integrated Photovoltaic Electric Vehicles

The development of vehicle integrated photovoltaics-powered electric vehicles (VIPV-EV) significantly reduces CO2 emissions from the transport sector to realize a decarbonized society. Although long-distance driving of VIPV-EV without electricity charging is expected in sunny regions, driving distance of VIPV-EV is affected by climate conditions such as solar irradiation and temperature rise of PV modules. In this paper, detailed analytical results for effects of climate conditions such as solar irradiation and temperature rise of PV modules upon driving distance of the VIPV-EV were presented by using test data for Toyota Prius and Nissan Van demonstration cars installed with high-efficiency InGaP/GaAs/InGaAs 3-junction solar cell modules with a module efficiency of more than 30%. The temperature rise of some PV modules studied in this study was shown to be expressed by some coefficients related to solar irradiation, wind speed and radiative cooling. The potential of VIPV-EV to be deployed in 10 major cities was also analyzed. Although sunshine cities such as Phoenix show the high reduction ratio of driving range with 17% due to temperature rise of VIPV modules, populous cities such as Tokyo show low reduction ratio of 9%. It was also shown in this paper that the difference between the driving distance of VIPV-EV driving in the morning and the afternoon is due to PV modules’ radiative cooling. In addition, the importance of heat dissipation of PV modules and the development of high-efficiency PV modules with better temperature coefficients was suggested in order to expand driving range of VIPV-EV. The effects of air-conditioner usage and partial shading in addition to the effects of temperature rise of VIPV modules were suggested as the other power losses of VIPV-EV.

Numerical Assessment of the Thermal Efficiency of a Concentrated Photovoltaic/Thermal (CPV/T) Hybrid System Using Air as Heat Transfer Fluid

In this paper, we propose a thermal model of a hybrid photovoltaic/thermal concentration system. Starting from the thermal balance of the model, the equation is solved and simulated with a MATLAB code, considering air as the cooling fluid. This enabled us to evaluate some of the parameters influencing the electrical and thermal performance of this device. The results showed that the temperature, thermal efficiency and electrical efficiency delivered depend on the air mass flow rate. The electrical and thermal efficiencies for different values of air mass flow are encouraging, and demonstrate the benefits of cooling photovoltaic cells. The results show that thermal efficiency decreases air flow rate greater than 0.7 kg/s, whatever the value of the light concentration used. The thermal efficiency of the solar cell increases as the light concentration increases, whatever the air flow rate used. For a concentration equal to 30 sun, the thermal efficiency is 0.16 with an air flow rate equal to 0.005 kg/s;the thermal efficiency increases to 0.19 with an air flow rate equal to 0.1 kg/s at the same concentration. An interesting and useful finding was that the proposed numerical model allows the determination of the electrical as well as thermal efficiency of the hybrid CPV/T with air flow as cooling fluid.

基于TRNSYS的扁平热管PV/T系统性能优化

基于太阳能技术现状分析,将太阳能光伏组件与扁平式热管高效结合,提出新型扁平热管PV/T系统.为实现该系统综合效率最大化,结合TRNSYS仿真,开展试验并进行优化分析.结果表明,安装扁平热管后夏季热水温度从原来的51.1℃升高到57.3℃,提高了12.1%,冬季热水温度从47.6℃升高到55.2℃,提高了15.9%.夏季系统的综合效率提高了4.7%、冬季系统的综合效率提高了4.8%.可以得出结论扁平热管对PV/T空调系统性能的优化效果明显,也为该技术在建筑领域的应用提供了依据.

基于人工神经网络的PV/T热电联供系统性能预测

为研究太阳能PV/T热电联供系统的性能和针对太阳能PV/T系统复杂的能量平衡方程,搭建了太阳能PV/T系统试验台,同时建立了基于改进灰狼优化的BP神经网络(back propagation neural network model based on improved grey wolf algorithm,IGWO-BP)预测模型,在晴朗天气下进行试验,并采用该模型对系统电功率以及蓄热水箱内水温进行预测。结果显示,晴朗日系统的电效率8.7%~12.2%、热效率51.7%;预测结果与BP神经网络预测模型、基于粒子群优化的BP神经网络(back propagation neural network based on particle swarm optimization,PSO-BP)预测模型和卷积神经网络(convolutional neural network,CNN)预测模型预测结果进行比较,结果显示IGWO-BP预测模型电效率预测模型的绝对百分比误差(mean absolute percentage error,MAPE)、决定系数(determination coefficient,R^(2))、均方根误差(root mean square error,RMSE)、效率因子(efficient factor,EF)和Pearson相关系数(pearson related coefficient,r)分别为4.5E-05、0.99、0.24、0.99和1.00,在储热罐温度预测中,上述指标分别为8.90E-04、0.98、0.07、0.98、0.99,均优于其他预测模型,IGWO-BP神经网络预测模型具有更好的预测性能。研究结果可为太阳能PV/T热电联供系统性能预测与优化控制提供参考。

应用PSO-RBF神经网络预测太阳能PV/T系统的热、电性能

为准确预测太阳能光伏光热(Solar Photovoltaic/Thermal,PV/T)系统的热、电性能,文章利用PSO(Particle Swarm Optimization)算法优化了RBF(Radial Basis Function)神经网络,并基于此方法建立了太阳能PV/T系统性能的仿真预测模型,与基于未优化RBF神经网络建立的预测模型进行了对比分析。同时,搭建了太阳能PV/T实验平台,通过云平台采集实验数据用于上述模型。研究结果表明:使用PSO算法优化后的RBF神经网络模型相较于未优化模型预测精度提高了20%,预测稳定性提高了30%,拟合优度R值有所提升。基于PSO-RBF神经网络建立的预测模型可精确预测太阳能PV/T系统的热、电性能。

太阳能PV/T+相变能与直蒸式水源热泵供热(冷)系统特性分析

为解决河北农村建筑清洁供暖问题和太阳能利用具有不稳定性问题,设计了太阳能PV/T+相变能与直蒸式水源热泵供热(冷)系统进行实验研究。实验结果表明,冬季典型日系统发电量为4.453kWh,制热系数COP平均值3.41;夏季典型日系统发电量为5.945kWh,制冷系数EER平均值3.2;将发电量用于系统运行,制热系数COP为4.22,制冷系数EER为4.19,分别提高了23.75%和30.12%;夏季单纯PV/T太阳能电池发电量5.537kWh,本系统的发电量提高了7.37%。该系统经济效益高,运行稳定,是一种实现河北农村清洁供暖有效途径。

Performance Assessment of a Real PV System Connected to a Low-Voltage Grid

The generation of photovoltaic(PV)solar energy is increasing continuously because it is renewable,unlimited,and clean energy.In the past,generation systems depended on non-renewable sources such as oil,coal,and gas.Therefore,this paper assesses the performance of a 51 kW PV solar power plant connected to a low-voltage grid to feed an administrative building in the 6th of October City,Egypt.The performance analysis of the considered grid-connected PV system is carried out using power system simulator for Engineering(PSS/E)software.Where the PSS/E program,monitors and uses the power analyzer that displays the parameters and measures some parameters such as current,voltage,total power,power factor,frequency,and current and voltage harmonics,the used inverter from the type of grid inverter for the considered system.The results conclude that when the maximum solar radiation is reached,the maximum current can be obtained from the solar panels,thus obtaining the maximum power and power factor.Decreasing total voltage harmonic distortion,a current harmonic distortion within permissible limits using active harmonic distortion because this type is fast in processing up to 300 microseconds.The connection between solar stations and the national grid makes the system more efficient.

基于PV/T的双源热泵热水系统的实验研究

为提高热泵热水循环的效率,构建基于光伏/光热一体化(PV/T)的双源热泵热水系统,选取全年中4个典型日,测试系统的可靠性、热泵运行性能以及PV/T运行特性。结果表明:系统的电源和热源可稳定使用;4个典型工况中,环境温度为27.3℃、太阳辐照度为975.6 W/m^(2)时热泵运行性能最优,制热系数(COPh)达到6.2,PV/T性能最优,平均光电转换效率相对于传统光伏组件高6.6%,总发电量比传统光伏组件高0.11 kWh。

Synergetic optimization operation method for distribution network based on SOP and PV

The integration of distributed generation brings in new challenges for the operation of distribution networks,including out-of-limit voltage and power flow control.Soft open points(SOP)are new power electronic devices that can flexibly control active and reactive power flows.With the exception of active power output,photovoltaic(PV)devices can provide reactive power compensation through an inverter.Thus,a synergetic optimization operation method for SOP and PV in a distribution network is proposed.A synergetic optimization model was developed.The voltage deviation,network loss,and ratio of photovoltaic abandonment were selected as the objective functions.The PV model was improved by considering the three reactive power output modes of the PV inverter.Both the load fluctuation and loss of the SOP were considered.Three multi-objective optimization algorithms were used,and a compromise optimal solution was calculated.Case studies were conducted using an IEEE 33-node system.The simulation results indicated that the SOP and PVs complemented each other in terms of active power transmission and reactive power compensation.Synergetic optimization improves power control capability and flexibility,providing better power quality and PV consumption rate.

PV/T耦合水环热泵系统全年运行性能分析

为研究裸板型PV/T组件与水环热泵耦合系统的电热联供性能,本文基于天津某办公楼的零碳化改造项目,搭建了PV/T耦合水箱、水环热泵,通过温差控制,实现PV/T集散热独立循环,耦合热泵制热和制冷,以满足建筑多种用能需求的低碳能源系统。测试分析了冬季典型日、夏季典型日,PV、PV/T和水箱内的温度变化特性,PV/T、PV系统的发电功率、发电效率、PV/T的集热效率以及综合效率,比较了PV/T系统和PV系统的性能。结果显示,在冬季典型日,PV/T组件与PV组件的平均温差达16.1℃,PV/T发电效率较PV提高了2.2%,PV/T集热效率为42.2%,综合效率为52.6%,系统平均性能系数为6.06;在夏季典型日,PV/T发电效率较PV提高了3.8%,PV/T集热效率为59.1%,综合效率最高为73.6%,系统平均性能系数为6.86。研究表明,PV/T耦合水环热泵系统全年较PV发电效率可提高2%以上,集热效率>40%,系统平均性能系数>6.0,具有较强的节能减排特点。

“双碳”背景下BIPV的应用与探索

“双碳”目标提出后,中国的绿色经济发展有了更加明确的方向。城镇化率不断增长的同时,中国的建筑业进入了鼎盛发展时期;但与此同时出现的建筑能耗问题也越来越严重,这种发展形式与“双碳”目标背道而驰。而光伏发电技术与建筑相结合成为解决这一问题的有效方式,光伏建筑一体化(BIPV)产业的发展是实现“双碳”目标的重要途径。针对当前BIPV产业的发展状况及发展优势进行了分析,并分析了影响BIPV建筑发电量的因素,然后从技术、法律法规、市场3个方面提出了优化举措。分析结果显示:光伏组件方位角及安装倾角、光伏组件表面灰尘及其安装方式是制约BIPV建筑发电量的主要因素,BIPV后续发展需要从技术方面进行改进以确保年发电量达到预期目标;BIPV产业应从技术、法律法规及市场3个方面进行改进和完善,有助于其更好的发展。该研究结果对BIPV理论研究和工程人员施工设计具有一定的参考价值。

太阳能光伏光热PV/T组件在建筑设计中的应用

建筑领域“双碳”目标的提出,使得降低建筑能耗成为目前亟需解决的问题。可再生能源同建筑领域的有机结合被认为是解决建筑能耗的重要环节。通过对太阳能光伏光热技术的发展进行总结,研究太阳能光伏光热技术在建筑领域中的设计方法,提出了对未来光伏光热建筑一体化的设计思考,为以后太阳能光伏光热PV/T技术产业的发展提供参考。

Probabilistic Global Maximum Power Point Tracking Algorithm for Continuously Varying Partial Shading Conditions on Autonomous PV Systems

A photovoltaic (PV) string with multiple modules with bypass diodes frequently deployed on a variety of autonomous PV systems may present multiple power peaks under uneven shading. For optimal solar harvesting, there is a need for a control schema to force the PV string to operate at global maximum power point (GMPP). While a lot of tracking methods have been proposed in the literature, they are usually complex and do not fully take advantage of the available characteristics of the PV array. This work highlights how the voltage at operating point and the forward voltage of the bypass diode are considered to design a global maximum power point tracking (GMPPT) algorithm with a very limited global search phase called Fast GMPPT. This algorithm successfully tracks GMPP between 94% and 98% of the time under a theoretical evaluation. It is then compared against Perturb and Observe, Deterministic Particle Swarm Optimization, and Grey Wolf Optimization under a sequence of irradiance steps as well as a power-over-voltage characteristics profile that mimics the electrical characteristics of a PV string under varying partial shading conditions. Overall, the simulation with the sequence of irradiance steps shows that while Fast GMPPT does not have the best convergence time, it has an excellent convergence rate as well as causes the least amount of power loss during the global search phase. Experimental test under varying partial shading conditions shows that while the GMPPT proposal is simple and lightweight, it is very performant under a wide range of dynamically varying partial shading conditions and boasts the best energy efficiency (94.74%) out of the 4 tested algorithms.

基于TRNSYS的学校建筑PV/T跨季节蓄热供暖研究

PV/T耦合地源热泵系统在多能互补、提高可再生能源利用率方面受到广泛的关注,针对南京市某小学工程应用PV/T耦合地源热泵系统实现跨季节供暖做模拟分析。应用TRNSYS软件针对系统的运行温度、集热效率、设备工况、能源利用率进行模拟。发现PV/T电池通过地埋管放热的冷却水具有较好的集热冷却效果;土壤蓄热体平均温度仅下降0.23℃,实现土壤热平衡,且该系统的跨季节蓄热率约为60%;热泵机组实际COP平均COP在5以上,具有良好的节能效果;系统跨季节可以提供建筑热负荷的73.17%,发电量可以满足63.2%的热泵能耗。

Analysis of the Effect of Temperature and Relative Humidity on the Reliability of a Photovoltaic Module

Photovoltaic energy occupies a significant place in the renewable energy market, with photovoltaic (PV) modules playing a vital role in converting solar energy into electricity. However, their effectiveness is likely to be affected by variations in environmental conditions, including temperature and relative humidity. The study examines the impact of these major climatic factors on the reliability of PV modules, aiming to provide crucial information for optimizing and managing these systems under varying conditions. Inspired by Weibull’s law to model the lifespan of components, we proposed a mathematical model integrating a correction factor linked to temperature and relative humidity. Using this approach, simulations in Matlab Simulink reveal that increasing temperature and relative humidity have an adverse impact on the reliability and lifespan of PV modules, with a more pronounced impact on temperature. The results highlight the importance of considering these environmental parameters in the management and optimization of photovoltaic systems to ensure their long-term efficiency.

Stability Study of Low Voltage Electrical Distribution Network: Audit and Improvement of DJEGBE Mini Solar Photovoltaic Power Plant in the Commune of OUESSE (Benin)

The supply of quality energy is a major concern for distribution network managers. This is the case for the company ASEMI, whose subscribers on the DJEGBE mini-power station network are faced with problems of current instability, voltage drops, and repetitive outages. This work is part of the search for the stability of the electrical distribution network by focusing on the audit of the DJEGBE mini photovoltaic solar power plant electrical network in the commune of OUESSE (Benin). This aims to highlight malfunctions on the low-voltage network to propose solutions for improving current stability among subscribers. Irregularities were noted, notably the overloading of certain lines of the PV network, implying poor distribution of loads by phase, which is the main cause of voltage drops;repetitive outages linked to overvoltage caused by lightning and overcurrent due to overload;faulty meters, absence of earth connection at subscribers. Peaks in consumption were obtained at night, which shows that consumption is greater in the evening. We examined the existing situation and processed the data collected, then simulated the energy consumption profiles with the network analyzer “LANGLOIS 6830” and “Excel”. The power factor value recorded is an average of 1, and the minimum value is 0.85. The daily output is 131.08 kWh, for a daily demand of 120 kWh and the average daily consumption is 109.92 kWh, or 83.86% of the energy produced per day. These results showed that the dysfunctions are linked to the distribution and the use of produced energy. Finally, we proposed possible solutions for improving the electrical distribution network. Thus, measures without investment and those requiring investment have been proposed.

Maximizing Solar Potential Using the Differential Grey Wolf Algorithm for PV System Optimization

Maximum Power Point Tracking(MPPT)is crucial for maximizing the energy output of photovoltaic(PV)systems by continuously adjusting the operating point of the panels to track the point of maximum power production under changing environmental conditions.This work proposes the design of an MPPT system for solar PV installations using the Differential Grey Wolf Optimizer(DGWO).It dynamically adjusts the parameters of the MPPT controller,specifically the duty cycle of the SEPIC converter,to efficiently track the Maximum Power Point(MPP).The proposed system aims to enhance the energy harvesting capability of solar PV systems by optimizing their performance under varying solar irradiance,temperature and shading conditions.Simulation results demonstrate the effectiveness of the DGWO-based MPPT system in maximizing the power output of solar PV installations compared to conventional MPPT methods.This research contributes to the development of advanced MPPT techniques for improving the efficiency and reliability of solar energy systems.

Inter-Row Spacing of PV Power Plant

When designing a solar power plant, it is much more important to avoid the shadow on the PV Panels. As the shadow falls on the PV Panels;it significantly reduces the generation of required power as planned and designed. This research paper and case study will help a lot to avoid shadow, especially when selecting inter-row spacing between the strings of solar power plants.

Maximum Power Point Tracking Technology for PV Systems: Current Status and Perspectives

Maximum power point tracking(MPPT)technology plays a key role in improving the energy conversion efficiency of photovoltaic(PV)systems,especially when multiple local maximum power points(LMPPs)occur under partial shading conditions(PSC).It is necessary to modify the operating point efficiently and accurately with the help of MPPT technology to maximize the collected power.Even though a lot of research has been carried out and impressive progress achieved for MPPT technology,it still faces some challenges and dilemmas.Firstly,the mathematical model established for PV cells is not precise enough.Second,the existing algorithms are often optimized for specific conditions and lack comprehensive adaptability to the actual operating environment.Besides,a single algorithm may not be able to give full play to its advantages.In the end,the selection criteria for choosing the suitable MPPT algorithm/converter combination to achieve better performance in a given scenario is very limited.Therefore,this paper systematically discusses the current research status and challenges faced by PV MPPT technology around the three aspects of MPPT models,algorithms,and hardware implementation.Through in-depth thinking and discussion,it also puts forward positive perspectives on future development,and five forward-looking solutions to improve the performance of PV systems MPPT are suggested.